Final Project - Indicators of Anxiety or Depression Based on Reported Frequency of Symptoms During Last 7 Days

Reseach Question: How did anxiety and depression levels differ between states following the outbreak of COVID-19 in the United States?

Data Cleaning

Import libraries and dataset

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px

df = pd.read_csv("./Datasets/Indicators_of_Anxiety_or_Depression_Based_on_Reported_Frequency_of_Symptoms_During_Last_7_Days.csv")

df.head()

	Indicator	Group	State	Subgroup	Phase	Time Period	Time Period Label	Time Period Start Date	Time Period End Date	Value	Low CI	High CI	Confidence Interval	Quartile Range
0	Symptoms of Depressive Disorder	National Estimate	United States	United States	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	23.5	22.7	24.3	22.7 - 24.3	NaN
1	Symptoms of Depressive Disorder	By Age	United States	18 - 29 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	32.7	30.2	35.2	30.2 - 35.2	NaN
2	Symptoms of Depressive Disorder	By Age	United States	30 - 39 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	25.7	24.1	27.3	24.1 - 27.3	NaN
3	Symptoms of Depressive Disorder	By Age	United States	40 - 49 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	24.8	23.3	26.2	23.3 - 26.2	NaN
4	Symptoms of Depressive Disorder	By Age	United States	50 - 59 years	1	1	Apr 23 - May 5, 2020	04/23/2020	05/05/2020	23.2	21.5	25.0	21.5 - 25.0	NaN

Filter to only state data and drop unnecessary columns;Group and Subgroup are redundant, Time period and CI are just combinations of other column’s data.

state_data = df[df['Group']=='By State']

state_data.drop(columns = ['Group', 'Subgroup', 'Time Period Label', 'Confidence Interval'], inplace = True)

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\4290850861.py:3: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

Seperate Quartile Range into 2 Columns:

state_data[['Quartile_Lower', 'Quartile_Upper']] = state_data['Quartile Range'].str.split(' - ', expand=True)
state_data.drop(columns='Quartile Range')

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\3542449001.py:1: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\3542449001.py:1: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

	Indicator	State	Phase	Time Period	Time Period Start Date	Time Period End Date	Value	Low CI	High CI	Quartile_Lower	Quartile_Upper
19	Symptoms of Depressive Disorder	Alabama	1	1	04/23/2020	05/05/2020	18.6	14.6	23.1	16.5	20.7
20	Symptoms of Depressive Disorder	Alaska	1	1	04/23/2020	05/05/2020	19.2	16.8	21.8	16.5	20.7
21	Symptoms of Depressive Disorder	Arizona	1	1	04/23/2020	05/05/2020	22.4	19.4	25.5	22.2	24.0
22	Symptoms of Depressive Disorder	Arkansas	1	1	04/23/2020	05/05/2020	26.6	22.3	31.3	24.1	28.7
23	Symptoms of Depressive Disorder	California	1	1	04/23/2020	05/05/2020	25.4	22.5	28.6	24.1	28.7
...	...	...	...	...	...	...	...	...	...	...	...
14368	Symptoms of Anxiety Disorder or Depressive Dis...	Virginia	3.10	62	09/20/2023	10/02/2023	33.2	29.8	36.7	30.7-33.5	None
14369	Symptoms of Anxiety Disorder or Depressive Dis...	Washington	3.10	62	09/20/2023	10/02/2023	34.3	31.0	37.7	33.6-36.2	None
14370	Symptoms of Anxiety Disorder or Depressive Dis...	West Virginia	3.10	62	09/20/2023	10/02/2023	44.7	40.0	49.4	36.3-44.7	None
14371	Symptoms of Anxiety Disorder or Depressive Dis...	Wisconsin	3.10	62	09/20/2023	10/02/2023	30.4	27.1	33.9	24.5-30.6	None
14372	Symptoms of Anxiety Disorder or Depressive Dis...	Wyoming	3.10	62	09/20/2023	10/02/2023	36.3	30.1	42.9	36.3-44.7	None

9486 rows × 11 columns

Clean up the Phase column:

state_data['Phase'].unique()
# There are 2 values that contain dates which are already stored in other columns, so we can remove these dates

state_data['Phase'] = state_data['Phase'].str.split(' ', expand = True).get(0)

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\3952733264.py:4: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

Change Data Types as needed

state_data['Indicator'] = pd.Categorical(state_data['Indicator'], categories = ['Symptoms of Depressive Disorder', 'Symptoms of Anxiety Disorder', 'Symptoms of Anxiety Disorder or Depressive Disorder'])

state_data['Phase'] = pd.Categorical(state_data['Phase'], categories=['1', '2', '3', '3.1', '3.2', '3.3', '3.4', '3.5', '3.6', '3.7', '3.8', '3.9', '3.10'])

state_data['Time Period Start Date'] = pd.to_datetime(state_data['Time Period Start Date']).dt.date
state_data['Time Period End Date'] = pd.to_datetime(state_data['Time Period End Date']).dt.date

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\2391328660.py:1: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\2391328660.py:3: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\2391328660.py:5: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\2391328660.py:6: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

EDA

Looking at some graphs

# Histogram of values for all states
plt1 = sns.histplot(state_data, x='Value', hue = 'Indicator', alpha = 0.5)
plt.title('Histogram of Value by Indicator')
plt.show()

# Pair Plot
pair_plot = sns.pairplot(state_data[['Indicator','Value','Time Period']], hue = 'Indicator')
plt.show()

national_avgs = state_data.groupby(['Time Period Start Date', 'Indicator']).agg(
    nat_means = ('Value', 'mean')
)
nat_avg_plt = sns.lineplot(national_avgs,
                            x='Time Period Start Date',
                            y='nat_means',
                            hue = 'Indicator')
plt.xticks(rotation=45)
plt.title(f"Values Over Time")
plt.ylabel('Values')
plt.show()

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\477478972.py:1: FutureWarning:

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.

state_code_map = {
    "Alabama": "AL",
    "Alaska": "AK",
    "Arizona": "AZ",
    "Arkansas": "AR",
    "California": "CA",
    "Colorado": "CO",
    "Connecticut": "CT",
    "Delaware": "DE",
    "Florida": "FL",
    "Georgia": "GA",
    "Hawaii": "HI",
    "Idaho": "ID",
    "Illinois": "IL",
    "Indiana": "IN",
    "Iowa": "IA",
    "Kansas": "KS",
    "Kentucky": "KY",
    "Louisiana": "LA",
    "Maine": "ME",
    "Maryland": "MD",
    "Massachusetts": "MA",
    "Michigan": "MI",
    "Minnesota": "MN",
    "Mississippi": "MS",
    "Missouri": "MO",
    "Montana": "MT",
    "Nebraska": "NE",
    "Nevada": "NV",
    "New Hampshire": "NH",
    "New Jersey": "NJ",
    "New Mexico": "NM",
    "New York": "NY",
    "North Carolina": "NC",
    "North Dakota": "ND",
    "Ohio": "OH",
    "Oklahoma": "OK",
    "Oregon": "OR",
    "Pennsylvania": "PA",
    "Rhode Island": "RI",
    "South Carolina": "SC",
    "South Dakota": "SD",
    "Tennessee": "TN",
    "Texas": "TX",
    "Utah": "UT",
    "Vermont": "VT",
    "Virginia": "VA",
    "Washington": "WA",
    "West Virginia": "WV",
    "Wisconsin": "WI",
    "Wyoming": "WY",
    "District of Columbia": "DC",
    "American Samoa": "AS",
    "Guam": "GU",
    "Northern Mariana Islands": "MP",
    "Puerto Rico": "PR",
    "United States Minor Outlying Islands": "UM",
    "Virgin Islands, U.S.": "VI",
}

indicators = state_data['Indicator'].unique()
color_scales = ['blues','amp','purp']

for i,j in zip(indicators,color_scales):
    fig_data = state_data[(state_data['Indicator'] == i)]

    fig_data['State_Code'] = fig_data['State'].map(state_code_map)

    max = fig_data['Value'].max()
    min = fig_data['Value'].min()

    fig = px.choropleth(
        fig_data,
        locations='State_Code',
        locationmode='USA-states',
        color='Value',
        scope='usa',
        title=f'Map of {i} in US states',
        hover_name='State',
        color_continuous_scale=j,
        animation_frame='Time Period Start Date',
        range_color=[min,max]
    )
    fig.show()

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\1124955677.py:67: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\1124955677.py:67: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

C:\Users\ianwa\AppData\Local\Temp\ipykernel_17852\1124955677.py:67: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy